Optimal fuzzy PID controller design for an active magnetic bearing system based on adaptive genetic algorithms

摘要

We propose an adaptive genetic algorithm (AGA) for the multi-objective optimisation designrnof a fuzzy PID controller and apply it to the control of an active magnetic bearing (AMB)rnsystem. Unlike PID controllers with fixed gains, a fuzzy PID controller is expressed in termsrnof fuzzy rules whose consequences employ analytical PID expressions. The PID gains arernadaptive and the fuzzy PID controller has more flexibility and capability than conventionalrnones. Moreover, it can be easily used to develop a precise and fast control algorithm in anrnoptimal design. An adaptive genetic algorithm is proposed to design the fuzzy PIDrncontroller. The centres of the triangular membership functions and the PID gains for allrnfuzzy control rules are selected as parameters to be determined. We also present a dynamicrnmodel of an AMB system for axial motion. The simulation results of this AMB system showrnthat a fuzzy PID controller designed using the proposed AGA has good performance.